dados_radar_extremo_3h.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "dados_radar_extremo.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyMg8cLmuMrDfSnJ2b1Lvxy7",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/MLRG-CEFET-RJ/attention-mechanism/blob/main/dados_radar_extremo_3h.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TJFRm1d8nRKD",
        "outputId": "b9eb8b0b-49dd-455f-f4c0-511c502d537c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: wradlib in /usr/local/lib/python3.7/dist-packages (1.13.0)\n",
            "Requirement already satisfied: dask in /usr/local/lib/python3.7/dist-packages (from wradlib) (2.12.0)\n",
            "Requirement already satisfied: gdal in /usr/local/lib/python3.7/dist-packages (from wradlib) (2.2.2)\n",
            "Requirement already satisfied: deprecation in /usr/local/lib/python3.7/dist-packages (from wradlib) (2.1.0)\n",
            "Requirement already satisfied: xarray>=0.17.0 in /usr/local/lib/python3.7/dist-packages (from wradlib) (0.18.2)\n",
            "Requirement already satisfied: netCDF4 in /usr/local/lib/python3.7/dist-packages (from wradlib) (1.5.8)\n",
            "Requirement already satisfied: h5netcdf in /usr/local/lib/python3.7/dist-packages (from wradlib) (0.13.1)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.7/dist-packages (from wradlib) (1.4.1)\n",
            "Requirement already satisfied: h5py in /usr/local/lib/python3.7/dist-packages (from wradlib) (3.1.0)\n",
            "Requirement already satisfied: xmltodict in /usr/local/lib/python3.7/dist-packages (from wradlib) (0.12.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from wradlib) (2.23.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from wradlib) (1.19.5)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.7/dist-packages (from wradlib) (3.2.2)\n",
            "Requirement already satisfied: pandas>=1.0 in /usr/local/lib/python3.7/dist-packages (from xarray>=0.17.0->wradlib) (1.3.5)\n",
            "Requirement already satisfied: setuptools>=40.4 in /usr/local/lib/python3.7/dist-packages (from xarray>=0.17.0->wradlib) (57.4.0)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=1.0->xarray>=0.17.0->wradlib) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=1.0->xarray>=0.17.0->wradlib) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=1.0->xarray>=0.17.0->wradlib) (1.15.0)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from deprecation->wradlib) (21.3)\n",
            "Requirement already satisfied: cached-property in /usr/local/lib/python3.7/dist-packages (from h5py->wradlib) (1.5.2)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->wradlib) (1.3.2)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib->wradlib) (0.11.0)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->wradlib) (3.0.7)\n",
            "Requirement already satisfied: cftime in /usr/local/lib/python3.7/dist-packages (from netCDF4->wradlib) (1.5.2)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->wradlib) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->wradlib) (2021.10.8)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->wradlib) (2.10)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->wradlib) (3.0.4)\n"
          ]
        }
      ],
      "source": [
        "!pip install wradlib"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "XloYH7rXn75Y",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "edffce5c-0d1e-4ebf-c929-8d34b9ec76c0"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "metadata": {
        "id": "Mzih7MRDn-vD"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import wradlib as wrl\n",
        "import os\n",
        "import numpy as np\n",
        "import tarfile\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.animation import FuncAnimation\n",
        "from glob import glob\n",
        "from IPython.display import HTML"
      ],
      "metadata": {
        "id": "Ms-rQ74yoA06"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "path = '/content/drive/MyDrive/Colab Notebooks'\n",
        "tar_filename = os.path.join(path, 'radar 3hrs.tar')\n",
        "vol_pattern = os.path.join(path, '*.vol')\n",
        "with tarfile.open(tar_filename, 'r') as tar_file:\n",
        "    tar_file.extractall(path)"
      ],
      "metadata": {
        "id": "aAl7NfwmoCs3"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "rainbow_files = glob(vol_pattern)"
      ],
      "metadata": {
        "id": "Fu0X4gYjqAd2"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def read_radar_data(filename):\n",
        "  data = wrl.io.read_rainbow(filename)\n",
        "  return data"
      ],
      "metadata": {
        "id": "mRsBl4WvqA9R"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_sensor_info(radar):\n",
        "  sensor_info = radar['volume']['sensorinfo']\n",
        "  name = sensor_info['@name']\n",
        "  lat = sensor_info['lat']\n",
        "  lon = sensor_info['lon']\n",
        "  return (name, lat, lon)"
      ],
      "metadata": {
        "id": "-WKiJmdbqCsH"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_slices(radar):\n",
        "  return radar['volume']['scan']['slice']"
      ],
      "metadata": {
        "id": "M3swMOBQqFTA"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_one_slice(radar, num=0):\n",
        "  return get_slices(radar)[num]"
      ],
      "metadata": {
        "id": "HuIlJ6s0qGwn"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_azimuthal_data(slice_):\n",
        "  ray_info = slice_['slicedata']['rayinfo']\n",
        "  azi_data = ray_info['data']\n",
        "  azi_depth = float(ray_info['@depth'])\n",
        "  azi_range = float(ray_info['@rays'])\n",
        "  elevation_angle = float(slice_['posangle'])\n",
        "  azi_data = (azi_data * azi_range / 2 ** azi_depth)\n",
        "  return {\n",
        "      'azi_data': azi_data,\n",
        "      'azi_depth': azi_depth,\n",
        "      'azi_range': azi_range,\n",
        "      'elevation_angle': elevation_angle\n",
        "  }"
      ],
      "metadata": {
        "id": "1uXl3K9BqH9P"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def define_range(slice_):\n",
        "  stoprange = float(slice_['stoprange'])\n",
        "  rangestep = float(slice_['rangestep'])\n",
        "  range = np.arange(0, stoprange, rangestep)\n",
        "  return range"
      ],
      "metadata": {
        "id": "bB0qLcmyqKVn"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_reflectivity(slice_, num=0):\n",
        "  rawdata = slice_['slicedata']['rawdata'][num]\n",
        "  data = rawdata['data']\n",
        "  data_depth = float(rawdata['@depth'])\n",
        "  data_min = float(rawdata['@min'])\n",
        "  data_max = float(rawdata['@max'])\n",
        "  data = data_min + data * (data_max - data_min) / 2 ** data_depth\n",
        "  return data"
      ],
      "metadata": {
        "id": "HMmzNK-KqLA_"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_radar_data(reflectivity, range, azi_data, elevation_angle, sensor_name, \n",
        "                    lat, lon):\n",
        "  ax, pm = wrl.vis.plot_ppi(reflectivity, r=range, az=azi_data, fig=fig);\n",
        "  title = f'{sensor_name}\\n day: 14/02/2018, time: 19:00 until 23:55\\n elevation angle: {elevation_angle} \\n{lat}N {lon}E'\n",
        "  plt_title = plt.title(title, fontsize=14);\n",
        "  plt_title.set_y(1.05);\n",
        "  cbar = plt.gcf().colorbar(pm, pad=0.075, shrink=0.75);\n",
        "  cbar.set_label('reflectivity [dBz]')\n",
        "  ax.set_xlabel('x_range [km]');\n",
        "  ax.set_ylabel('y_range [km]');\n",
        "  return ax"
      ],
      "metadata": {
        "id": "hNImH-oXqMKh"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def animate(i, sensor_name, lat, lon):\n",
        "  radar_data = read_radar_data(rainbow_files[i])\n",
        "  elevation_slice = get_one_slice(radar_data)\n",
        "  azi_dict = get_azimuthal_data(elevation_slice)\n",
        "  range = define_range(elevation_slice)\n",
        "  reflectivity = get_reflectivity(elevation_slice)\n",
        "  fig.clear()\n",
        "  image = plot_radar_data(reflectivity, range, azi_dict['azi_data'], \n",
        "                       azi_dict['elevation_angle'], sensor_name, lat, lon)\n",
        "  return image"
      ],
      "metadata": {
        "id": "0SjLutOnqOqX"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sensor_name, lat, lon = get_sensor_info(read_radar_data(rainbow_files[0]))"
      ],
      "metadata": {
        "id": "5ieao9QJqRs5"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "fig = plt.figure(figsize=(8,8));\n",
        "anim = FuncAnimation(fig, animate, frames=len(rainbow_files), interval=250, \n",
        "                     fargs=(sensor_name, lat, lon), blit=False);\n",
        "animation_control = HTML(anim.to_jshtml())"
      ],
      "metadata": {
        "id": "LkDRsp8_qV2Z",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 362
        },
        "outputId": "97a021f6-4750-4a74-f4a1-320c06a9b9a7"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "error",
          "ename": "KeyError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-17-c578b221b73f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m anim = FuncAnimation(fig, animate, frames=len(rainbow_files), interval=250, \n\u001b[1;32m      3\u001b[0m                      fargs=(sensor_name, lat, lon), blit=False);\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0manimation_control\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mHTML\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0manim\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_jshtml\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/animation.py\u001b[0m in \u001b[0;36mto_jshtml\u001b[0;34m(self, fps, embed_frames, default_mode)\u001b[0m\n\u001b[1;32m   1380\u001b[0m                                     \u001b[0membed_frames\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0membed_frames\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1381\u001b[0m                                     default_mode=default_mode)\n\u001b[0;32m-> 1382\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwriter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mwriter\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1383\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_html_representation\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_text\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1384\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/animation.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(self, filename, writer, fps, dpi, codec, bitrate, extra_args, metadata, extra_anim, savefig_kwargs, progress_callback)\u001b[0m\n\u001b[1;32m   1146\u001b[0m                     \u001b[0;32mfor\u001b[0m \u001b[0manim\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0md\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_anim\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1147\u001b[0m                         \u001b[0;31m# TODO: See if turning off blit is really necessary\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1148\u001b[0;31m                         \u001b[0manim\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_draw_next_frame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0md\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mblit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1149\u001b[0m                         \u001b[0;32mif\u001b[0m \u001b[0mprogress_callback\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1150\u001b[0m                             \u001b[0mprogress_callback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframe_number\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtotal_frames\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/animation.py\u001b[0m in \u001b[0;36m_draw_next_frame\u001b[0;34m(self, framedata, blit)\u001b[0m\n\u001b[1;32m   1186\u001b[0m         \u001b[0;31m# post- draw, as well as the drawing of the frame itself.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1187\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_pre_draw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframedata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mblit\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1188\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_draw_frame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframedata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1189\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_post_draw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframedata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mblit\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1190\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/matplotlib/animation.py\u001b[0m in \u001b[0;36m_draw_frame\u001b[0;34m(self, framedata)\u001b[0m\n\u001b[1;32m   1764\u001b[0m         \u001b[0;31m# Call the func with framedata and args. If blitting is desired,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1765\u001b[0m         \u001b[0;31m# func needs to return a sequence of any artists that were modified.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1766\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drawn_artists\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframedata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1767\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_blit\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1768\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drawn_artists\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-15-d18e0970bfa3>\u001b[0m in \u001b[0;36manimate\u001b[0;34m(i, sensor_name, lat, lon)\u001b[0m\n\u001b[1;32m      4\u001b[0m   \u001b[0mazi_dict\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_azimuthal_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0melevation_slice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m   \u001b[0mrange\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdefine_range\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0melevation_slice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m   \u001b[0mreflectivity\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_reflectivity\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0melevation_slice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m   \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclear\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m   image = plot_radar_data(reflectivity, range, azi_dict['azi_data'], \n",
            "\u001b[0;32m<ipython-input-13-0451012bd763>\u001b[0m in \u001b[0;36mget_reflectivity\u001b[0;34m(slice_, num)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mget_reflectivity\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mslice_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m   \u001b[0mrawdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mslice_\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'slicedata'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'rawdata'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnum\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m   \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrawdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'data'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m   \u001b[0mdata_depth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrawdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'@depth'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m   \u001b[0mdata_min\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrawdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'@min'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: 0"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "animation_control"
      ],
      "metadata": {
        "id": "tJPDe4S7qWUG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 172
        },
        "outputId": "f2b5c215-cda6-41af-815e-4ce8b3201746"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-18-9b20a0cb927d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0manimation_control\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m: name 'animation_control' is not defined"
          ]
        }
      ]
    }
  ]
}